Multi-signal Accelerated Degradation Testing of Rolling Ball Bearings Through Radial Overload

102 Pages·2016·17.24 MB·English

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Masters Theses Graduate School
5-2016
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Anna Marie Mazzolini
University of Tennessee - Knoxville, [email protected]
Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes
Part of the Nuclear Engineering Commons
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Mazzolini, Anna Marie, "Multi-signal Accelerated Degradation Testing of Rolling Ball Bearings Through
Radial Overload. " Master's Thesis, University of Tennessee, 2016.
https://trace.tennessee.edu/utk_gradthes/3787
This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and
Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE:
Tennessee Research and Creative Exchange. For more information, please contact [email protected].
To the Graduate Council:
I am submitting herewith a thesis written by Anna Marie Mazzolini entitled "Multi-signal
Accelerated Degradation Testing of Rolling Ball Bearings Through Radial Overload." I have
examined the final electronic copy of this thesis for form and content and recommend that it be
accepted in partial fulfillment of the requirements for the degree of Master of Science, with a
major in Nuclear Engineering.
Jamie B. Coble, Major Professor
We have read this thesis and recommend its acceptance:
J. Wesley Hines, Guillermo I. Maldonado
Accepted for the Council:
Carolyn R. Hodges
Vice Provost and Dean of the Graduate School
(Original signatures are on file with official student records.)
Multi-signal Accelerated Degradation Testing of
Rolling Ball Bearings Through Radial Overload

A Thesis Presented for the
Master of Science
Degree
The University of Tennessee, Knoxville

Anna Marie Mazzolini
May 2016
Copyright © 2016 by Anna Marie Mazzolini
All rights reserved.

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ACKNOWLEDGEMENTS

I would like to thank my advisor and committee chair, Dr. Jamie Coble, of the
Nuclear Engineering department at the University of Tennessee. Her guidance
has been instrumental in the completion of this research. I’d like to thank
Analysis and Measurement Services (AMS) for their assistance with the bearing
testbed design, as well as Cody Walker for his assistance in assembling,
modifying, and running the bearing testbed. I would also like to thank the
University of Tennessee Mechanical Engineering Department machine shop for
their help with the machining of parts for the testbed. Finally, I would also like to
thank the other members of my graduate committee, Dr. J. Wesley Hines and Dr.
Ivan Maldonado.

Lastly I would like to thank my family and my loving boyfriend, Dylan, for their

unwavering support.

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ABSTRACT
Bearings are essential components in rotating machinery found in abundance in
nuclear power plants. Bearing failure in nuclear power plants can lead to
increased operations and maintenance costs and even plant trips. When
developing maintenance procedures, it is ideal to minimize costs and equipment
downtime while maximizing safety. Reactive, or run-to-failure, maintenance
minimizes maintenance costs at the expense of operation costs and safety.
Preventative, or time-based, maintenance maximizes safety and minimizes
operation costs at the expense of equipment downtime and maintenance costs.
Predictive, or condition-based, maintenance attempts to optimize overall costs
while maintaining system safety and reducing downtown.

Predictive maintenance uses online equipment condition assessment and
remaining useful life (RUL) predictions to schedule inspection and maintenance
actions. The development of methods for early and accurate RUL predictions for
bearings has the potential to transform maintenance planning in the nuclear
power industry, reducing operation and maintenance costs while maintaining or
improving overall system safety, reliability, and economics.

In order to develop robust RUL models, examples of run-to-failure data are
needed. Using data collected during accelerated degradation tests has the
advantages of being easily controlled and of providing ample data over relatively
a short test period. A testbed has been designed and constructed that incites
bearing failure through the application of a radial load. Several parameters are
monitored continuously and online, including motor current, shaft rotational
speed, acoustics and bearing vibration and temperature. Bearing maintenance in
nuclear power plants to date has relied on vibration data analysis performed at
defined inspection intervals. By including several process signals in the testbed
design, recommendations are made for online monitoring of bearings in nuclear
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power plants that would augment, or perhaps replace, the current maintenance
scheme with gains in safety, economics, and system reliability.

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TABLE OF CONTENTS

Chapter One: Introduction ..................................................................................... 1

1.1 Problem ........................................................................................................ 1

1.2 Organization of paper .................................................................................. 2

Chapter Two: Background and Literature Review ................................................. 3

2.1 Understanding rolling ball bearings .............................................................. 3

2.1.1 Dynamics of a rolling ball bearing ......................................................... 3

2.1.2 Failure of rolling ball bearings ............................................................... 4

2.2 Accelerated degradation bearing testing ..................................................... 7

2.2.1 Introduction of defect directly ................................................................ 7

2.2.2 Fluting .................................................................................................... 8

2.2.3 Application of radial force ...................................................................... 8

2.3 Important process signals in rolling ball bearing analysis ............................ 9

2.3.1 Vibration ................................................................................................ 9

2.3.2 Acoustics ............................................................................................. 10

2.3.3 Temperature ........................................................................................ 10

2.3.4 Current ................................................................................................ 10

2.4 Data analysis techniques for bearing monitoring ....................................... 11

2.4.1 Time domain analysis .......................................................................... 11

2.4.2 Frequency domain analysis ................................................................. 12

2.4.3 Time-frequency analysis ..................................................................... 13

2.5 Data analysis techniques for bearing prognostics ..................................... 15

Chapter Three: Methodology ............................................................................... 18

3.1 Design of the bearing testbed .................................................................... 18

3.1.1 Data acquisition ................................................................................... 20

3.1.2 Safety Shutoff System ......................................................................... 21

3.1.3 Bearing and grease specifications ...................................................... 22

3.2 Bearing testing process ............................................................................. 22

Chapter Four: Results and Discussion ................................................................ 25

4.1 Data substantiation .................................................................................... 25

4.1.1 Frequency domain analysis ................................................................. 26

4.1.2 Time domain statistical trending .......................................................... 29

4.2 Signal evaluation ........................................................................................ 36

4.3 Postmortem visual inspection .................................................................... 37

Chapter Five: Recommendations ........................................................................ 41

5.1 Potential testbed modifications .................................................................. 41

5.2 Data acquisition recommendations ............................................................ 41

5.3 Data analysis recommendations ................................................................ 42

Chapter Six: Conclusions .................................................................................... 44

References .......................................................................................................... 45

Appendices .......................................................................................................... 50

Appendix A: Frequency Domain Analysis ........................................................... 51

Appendix B: Time Domain Analysis .................................................................... 59

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Appendix C: Post-Mortem Analysis ..................................................................... 87

Vita ...................................................................................................................... 89

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LIST OF TABLES

Table 3.1. Bearing rig part specifications. ........................................................... 19

Table 3.2. Sensor specifications. ......................................................................... 20

Table 3.3. Bearing dimensions. ........................................................................... 22

Table 4.1. Bearing loading scheme. .................................................................... 25

Table 4.2. Bearing characteristic frequencies. .................................................... 26

Table 4.3. Bearing 2 statistical features correlation coefficients (1/3). ................ 36

Table 4.4. Bearing 2 statistical features correlation coefficients (2/3). ................ 39

Table 4.5. Bearing 2 statistical features correlation coefficients (3/3). ................ 40

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